Head of Commercial Analytics & NBA — Pharma

Tiger Analytics Inc.; United States; Remote; USD 250,000 - 400,000; Full time

Job summary

Tiger Analytics is seeking a seasoned analytics leader to drive advanced data science initiatives within the commercial pharma space. This role focuses on building and scaling NBA frameworks and omnichannel strategies to personalize HCP and patient journeys, improving commercial effectiveness and business impact.

You will lead end-to-end analytics delivery, mentor a team of data scientists, and collaborate with cross-functional stakeholders to deploy models into production in a regulated pharma

Qualifications

• 12+ years in Data Science/Advanced Analytics in pharma.
• Proven NBA or recommendation system experience.
• Lead and mentor data science teams.
• Strong stakeholder management and client-facing skills.
• Hands-on with Python/R/SQL and ML frameworks.
• Experience with AWS/Azure/GCP.

Responsibilities

• Lead end-to-end delivery of data science and advanced analytics solutions in the commercial pharma domain.
• Design and implement Next Best Action (NBA) models to optimize customer engagement and decision-making.
• Develop and scale omnichannel analytics frameworks, integrating data from CRM, digital, field, and marketing touchpoints.
• Partner with Sales, Marketing, Market Access to translate business problems into analytical solutions.
• Mentor and lead a team of data scientists and analysts.
• Oversee data pipelines, model deployment, and monitoring in production environments.

Skills

Data science leadership

Python/R/SQL

ML frameworks

Cloud platforms

Stakeholder management

Pharma data knowledge

Tools

Veeva CRM

Job description

Tiger Analytics is seeking a seasoned analytics leader to drive advanced data science initiatives within the commercial pharma space. This role focuses on building and scaling NBA frameworks and omnichannel strategies to personalize HCP and patient journeys, improving commercial effectiveness and business impact.

You will lead end-to-end analytics delivery, mentor a team of data scientists, and collaborate with cross-functional stakeholders to deploy models into production in a regulated pharma